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Python Articles
Page 552 of 852
How to turn off error bars in Seaborn Bar Plot using Matplotlib?
To turn off error bars in a Seaborn bar plot, we can take the following steps−Load an example dataset from the online repository (requires Internet).Show the point estimates and confidence intervals with bars.To display the figure, use show() method.Exampleimport seaborn as sns import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True df = sns.load_dataset('titanic') sns.barplot(x='class', y='age', hue='survived', data=df, ci=None) plt.show()Output
Read MoreHow to set "step" on axis X in my figure in Matplotlib Python 2.6.6?
To set Step on X-axis in a figure in Matplotlib Python, we can take the following Steps −StepsCreate a list of data points, x.Add a subplot to the current figure using subplot() method.Set xticks and ticklabels with rotation=45.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = [1, 2, 3, 4] y = [1.2, 1.9, 3.1, 4.2] plt.plot(x,y) ax1 = plt.subplot() ax1.set_xticks(x) ax1.set_xticklabels(["one", "two", "three", "four"], rotation=45) plt.show()Output
Read MoreHow to get the default blue colour of matplotlib.pyplot.scatter?
The default color of a scatter point is blue. To get the default blue color of matplotlib scatter point, we can annotate them using annotate() method.StepsCreate a figure and a set of subplots using subplots() method.Plot a scatter point at (-1, 1) location.Add some label for that point.Plot a scatter point at (-0.9, 1) location.Add some label for that point.Plot a scatter point at (1.9, 1) location.Add some label for that point.Scale the x and y axes using xlim and ylim method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ...
Read MoreHow to set same color for markers and lines in a Matplotlib plot loop?
To set the same color for markers and lines in a matplotlib, we can take the following Steps −Initialize m, n and x data points using numpy.Create a new figure or activate an existing figure using figure() method.Clear the figure using clf() method.Add a subplot to the current figure using subplot() method.Get a marker from a iterable marker type.Iterate a range from 1 to n.Plot the lines and markers in the loop using plot() method with the same marker and colors for a line.To display the figure, use show() method.Exampleimport numpy as np import itertools from matplotlib import pyplot as ...
Read MorePlot a rectangle with an edgecolor in Matplotlib
To put edgecolor of a rectangle in matplotlib, we can take the following Steps −Create a new figure or activate an existing figure using figure() method.Add a subplot method to the current axis.Create a rectangle instance using Rectangle() class with an edgecolor and linewidth of the edge.Add a rectangle path on the plot.To place the text in the rectangle, we can use text() method.Scale x and y axes using xlim() and ylim() methods.To display the figure, use show() method.Exampleimport matplotlib from matplotlib import pyplot as plt, patches plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111) ...
Read MoreCentering x-tick labels between tick marks in Matplotlib
To place labels between two ticks, we can take the following steps−Load some sample data, r.Create a copy of the array, cast to a specified type.Create a figure and a set of subplots using subplots() method.Plot date and r sample data.Set the locator of the major/minor ticker using set_major_locator() and set_minor_locator() methods.Set the locator of the major/minor formatter using set_major_locator() and set_minor_formatter() methods.Now, place the ticklabel at the center.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.cbook as cbook import matplotlib.dates as dates import matplotlib.ticker as ticker import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = ...
Read MoreHow to change a table's fontsize with matplotlib.pyplot?
To change a table's fontsize with matplotlib, we can use set_fontsize() method.StepsCreate a figure and a set of subplots, nrows=1 and ncols=1.Create random data using numpy.Create columns value.Make the axis tight and off.Initialize a variable fontsize to change the font size.Set the font size of the table using set_font_size() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, axs = plt.subplots(1, 1) data = np.random.random((10, 3)) columns = ("Column I", "Column II", "Column III") axs.axis('tight') axs.axis('off') the_table = axs.table(cellText=data, colLabels=columns, loc='center') the_table.auto_set_font_size(False) the_table.set_fontsize(10) plt.show()Output
Read MoreChanging Matplotlib subplot size/position after axes creation
To change subplot size or position after axes creation, we can take the following steps−Create a new figure or activate an existing figure using figure() method.Add an '~.axes.Axes' to the figure as part of a subplot arrangement using add_subplot() method.A grid layout to place subplots within a figure using GridSpec() class.Set the position of the grid specs.Set the subplotspec instance.Add an '~.axes.Axes' to the figure as part of a subplot arrangement using add_subplot() method, with gridspec instance.Adjust the padding between and around the subplots.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt from matplotlib import gridspec as ...
Read MoreHow to rotate Matplotlib annotation to match a line?
To rotate matplotlib annotation to match a line, we can take the following steps−Create a new figure or activate an existing figure using figure() method.Add an '~.axes.Axes' to the figure as part of a subplot arrangement using add_subplot() method.Initialize the variables, m (slope) and c (intercept).Create x and y data points using numpy.Calculate theta to make text rotation.Plot the line using plot() method with x and y.Place text on the line using text() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax ...
Read MoreHow do I close all the open pyplot windows (Matplotlib)?
plt.figure().close(): Close a figure window.close() by itself closes the current figureclose(h), where h is a Figure instance, closes that figureclose(num) closes the figure with number=numclose(name), where name is a string, closes the figure with that labelclose('all') closes all the figure windowsExamplefrom matplotlib import pyplot as plt fig = plt.figure() ax = fig.add_subplot() plt.show() plt.close()OutputNow, swap the statements "plt.show()" and "plt.close()" in the code. You wouldn't get to see any plot as the output because the plot would already have been closed.
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